Digital cameras have become ubiquitous and can be used to take both still images and video images. Object recognition, and, in particular, face recognition, is a desirable feature for digital cameras. It can also be desirable to provide object recognition, and, in particular, face recognition, with other devices, such as computers, personal data assistants (PDAs), mobile telephones, and the like. In some instances, these devices may include a digital camera. In other instances, the devices may receive a still or video image and perform object recognition on the image.
Face recognition is also closely associated with face detection, in which a generic face is sought in an image. Face recognition goes a step further, seeking to classify a face detected in an image as a particular face from a database of previously identified faces desired to be found.
In many conventional methods, faces are recognized by determining the Euclidean distance between the features of an input face image and the features of a set of reference face images (e.g., a gallery or library of face images.) The identity of the input face image is determined to be the reference face which is least distant and is below a minimum threshold of detection. Other mathematical methods, such as principal component analysis (PCA) or linear discriminant analysis (LCA) have been used to reduce the computational load of the analysis and to improve the robustness of recognition.